Robust Face Recognition
19 papers with code • 0 benchmarks • 4 datasets
Robust face recognition is the task of performing recognition in an unconstrained environment, where there is variation of view-point, scale, pose, illumination and expression of the face images.
( Image credit: MeGlass dataset )
Benchmarks
These leaderboards are used to track progress in Robust Face Recognition
MALF
UFDD
MeGlass
OCFR-LFW
Latest papers
Occlusion Robust Face Recognition Based on Mask Learning with PairwiseDifferential Siamese Network
Deep Convolutional Neural Networks (CNNs) have been pushing the frontier of the face recognition research in the past years.
Stacked Dense U-Nets with Dual Transformers for Robust Face Alignment
Face Analysis Project on MXNet
Face Synthesis for Eyeglass-Robust Face Recognition
A feasible method is to collect large-scale face images with eyeglasses for training deep learning methods.
Pose-Robust Face Recognition via Deep Residual Equivariant Mapping
penincillin/DREAM
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CVPR 2018
However, many contemporary face recognition models still perform relatively poor in processing profile faces compared to frontal faces.
Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition
First, we propose a multi-task Convolutional Neural Network (CNN) for face recognition where identity classification is the main task and pose, illumination, and expression estimations are the side tasks.
A Comprehensive Survey on Pose-Invariant Face Recognition
The capacity to recognize faces under varied poses is a fundamental human ability that presents a unique challenge for computer vision systems.
A Fast and Accurate Unconstrained Face Detector
N2ITN/Face2Vec
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First, a new image feature called Normalized Pixel Difference (NPD) is proposed.
Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition
To perform unconstrained face recognition robust to variations in illumination, pose and expression, this paper presents a new scheme to extract "Multi-Directional Multi-Level Dual-Cross Patterns" (MDML-DCPs) from face images.
Fast L1-Minimization Algorithms For Robust Face Recognition
L1-minimization refers to finding the minimum L1-norm solution to an underdetermined linear system b=Ax.
